HTBDC 2016 - High Throughput Big Data Computing

The workshop would focus on architectures, software and middleware for high throughput big data computing. It will also discuss various scientific, engineering and business applications involving big data.
Topics
Topics of interests include, but are not limited to:
Architectures:
Data Clouds, Data Grids, and Data Centers;
High performance data transfer and ingestion;
Security and protection of sensitive data;
Data Storage and file systems; from disks to NVRAM supports; NoSQL and other data stores;
Networking support for data-intensive computing;
Cluster architecture for managing big data;
GPU acceleration of big data processing;
Software and middleware:
Data-aware toolkits and middleware;
Service oriented architectures for data-intensive computing;
Accountability, QoS, and SLAs;
Performance measurement, analytic modeling, simulation;
Data capturing, management, and scheduling techniques;
Algorithms and Workflows suited for data and workflow preservation ;
Data- and process-based workflows and mining techniques for long term preservation in multi-disciplinary environments;
Data formats and interfaces to serve scientific communities;
Indexing of internet scale data;
Labeling big data collections;
Scheduling and management of data assimilation;
AI systems for handling big data;
Applications:
Data archives, digital libraries, and preservation;
Data-intensive applications and their challenges;
Data intensive computing in science, commerce, entertainment and medicine;
Capturing scalability, reliability and availability;
Data-intensive scientific discovery;
Preservation;
Scientific data-sets analysis;
Cloud services for big data;
Exascale data processing;